import { Turbopuffer } from "@turbopuffer/turbopuffer"; const tpuf = new Turbopuffer({ // API tokens are created in the dashboard https://turbopuffer.com/dashboard apiKey: process.env.TURBOPUFFER_API_KEY, // Pick the right region https://turbopuffer.com/docs/regions baseUrl: "https://gcp-us-central1.turbopuffer.com", }); const ns = tpuf.namespace(`fts-ts-1-${Date.now()}`); await ns.write({ upsert_columns: { id: [1, 2, 3], content: [ "turbopuffer is a fast search engine with FTS, filtering, and vector search support", "turbopuffer can store billions and billions of documents cheaper than any other search engine", "turbopuffer will support many more types of queries as it evolves. turbopuffer will only get faster.", ], }, schema: { content: { type: "string", // Enable BM25 with default settings // For all config options, see https://turbopuffer.com/docs/schema full_text_search: true, }, }, }); // Basic FTS search, to combine with vector search, see https://turbopuffer.com/docs/hybrid-search let results = await ns.query({ rank_by: ["content", "BM25", "turbopuffer"], top_k: 10, include_attributes: ["content"], }); // [3, 1, 2] is the default BM25 ranking based on document length and term frequency console.log(results); // Simple phrase matching filter, to limit results to documents that contain the terms "search" and "engine" results = await ns.query({ rank_by: ["content", "BM25", "turbopuffer"], top_k: 10, filters: ["content", "ContainsAllTokens", "search engine"], include_attributes: ["content"], }); // [1, 2] (same as above, but without document 3) console.log(results); const ns2 = tpuf.namespace("fts-ts-2"); // Advanced Example await ns2.write({ upsert_columns: { id: [1, 2, 3], title: [ "Getting Started with Python", "Advanced TypeScript Tips", "Python vs JavaScript", ], content: [ "Learn Python basics including variables, functions, and classes", "Discover advanced TypeScript features and type system tricks", "Compare Python and JavaScript for web development", ], tags: [ ["python", "programming", "beginner"], ["typescript", "javascript", "advanced"], ["python", "javascript", "comparison"], ], language: ["en", "en", "en"], publish_date: [1709251200, 1709337600, 1709424000], }, schema: { title: { type: "string", full_text_search: { // See all FTS indexing options at https://turbopuffer.com/docs/schema language: "english", stemming: true, remove_stopwords: true, case_sensitive: false, }, }, content: { type: "string", full_text_search: { language: "english", stemming: true, remove_stopwords: true, }, }, tags: { type: "[]string", full_text_search: { stemming: false, remove_stopwords: false, case_sensitive: true, }, }, }, }); // Advanced FTS search, to combine with vector search, see https://turbopuffer.com/docs/hybrid-search // In this example, hits on `title` and `tags` are weighted / boosted higher than hits on `content` results = await ns2.query({ // See all FTS query options at https://turbopuffer.com/docs/query rank_by: [ "Sum", [ ["Product", [3, ["title", "BM25", "python beginner"]]], ["Product", [2, ["tags", "BM25", "python beginner"]]], ["content", "BM25", "python beginner"], ], ], filters: [ "And", [ ["publish_date", "Gte", 1709251200], ["language", "Eq", "en"], ], ], top_k: 10, include_attributes: ["title", "content", "tags"], }); console.log(results);

Full-Text Search Guide